Even though recent MIL-based methods [1]}, [2]} have made considerable progress, the process of slicing a video into fixed segments [rgb]0,0,0in an coarse-grained manner regardless of its duration is prone to bury abnormal patterns as normal frames that usually constitute the majority, even in abnormal videos [3]}.
[rgb]0,0.,0However, by sampling with a smaller temporal scale [rgb]0,0,0in a fine-grained manner, the network may overemphasize on the most intense part of an anomaly but ignore the context around it. In reality, anomalous events often last for a while. With the assumption of minimum duration of anomalies,
[rgb]0,0.,0the MIL network is forced to pay more attention to the context around the most anomalous part.
